Predictions of critical transitions with non-stationary reduced order models

Franzke, Christian L.E.. 2013 Predictions of critical transitions with non-stationary reduced order models. Physica D: Nonlinear Phenomena, 262. 35-47. https://doi.org/10.1016/j.physd.2013.07.013

Before downloading, please read NORA policies.

Preview

Text (This article has been accepted for publication and will appear in a revised form in Physica D: Nonlinear Phenomena, published by Elsevier. Copyright Elsevier.)
1-s2.0-S0167278913002212-main.pdf - Accepted Version
Download (6MB) | Preview

Abstract/Summary

Here we demonstrate the ability of stochastic reduced order models to predict the statistics of non-stationary systems undergoing critical transitions. First, we show that the reduced order models are able to accurately predict the autocorrelation function and probability density functions (PDF) of higher dimensional systems with time-dependent slow forcing of either the resolved or unresolved modes. Second, we demonstrate that whether the system tips early or repeatedly jumps between the two equilibrium points (flickering) depends on the strength of the coupling between the resolved and unresolved modes and the time scale separation. Both kinds of behaviour have been found to preceed critical transitions in earlier studies. Furthermore, we demonstrate that the reduced order models are also able to predict the timing of critical transitions. The skill of various proposed tipping indicators are discussed.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1016/j.physd.2013.07.013
Programmes:	BAS Programmes > Polar Science for Planet Earth (2009 - ) > Environmental Change and Evolution
ISSN:	0167-2789
Additional Keywords:	Stochastic modeling; Tipping points; Model reduction; Non-stationarity; Bifurcation; Critical transition
NORA Subject Terms:	Mathematics
Date made live:	31 Jul 2013 09:07 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/502814

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1016/j.physd.2013.07.013

Programmes:

BAS Programmes > Polar Science for Planet Earth (2009 - ) > Environmental Change and Evolution

ISSN:

0167-2789

Additional Keywords:

Stochastic modeling; Tipping points; Model reduction; Non-stationarity; Bifurcation; Critical transition

NORA Subject Terms:

Mathematics